MinerU-Ecosystem

The official ecosystem toolkit for MinerU Open API

Empowering developers and AI agents with seamless document parsing capabilities — PDF · Word · PPT · Images · Web pages → Markdown / JSON · VLM+OCR dual engine · 109 languages · MCP Server · LangChain / RAGFlow / Dify / FastGPT native integration.

中文文档

MinerU-Ecosystem/
├── cli/                  # Command-line tool for document parsing
├── sdk/                  # Multi-language SDKs
│   ├── python/           #   Python SDK
│   ├── go/               #   Go SDK
│   └── typescript/       #   TypeScript SDK
├── langchain_mineru/     # LangChain document loader integration
├── llama-index-readers-mineru/     # LlamaIndex document reader integration
├── mcp/                  # Model Context Protocol server (Python)
└── skills/               # AI agent skills (Claude Code, OpenClaw, etc.)

I want to...
│
├── 🌐 Try it instantly, with no install and no code
│   └── Web App → https://mineru.net/OpenSourceTools/Extractor
│
├── 💻 Parse documents from the terminal
│   └── CLI → cli/
│       flash-extract: no token, best for quick previews
│       extract: full features, better for production workflows
│
├── 🐍 Integrate it into my Python / Go / TypeScript project
│   └── SDK → sdk/python/ | sdk/go/ | sdk/typescript/
│
├── 🤖 Enable my AI agent to parse documents
│   ├── Call the CLI directly → cli/
│   ├── Use natural-language skills (OpenClaw, ZeroClaw, etc.) → skills/
│   └── Use MCP protocol (Cursor, Claude Desktop, Windsurf, etc.) → mcp/
│
├── 📚 Build a RAG pipeline / knowledge base
│   ├── LangChain Loader → langchain_mineru/
│   └── LlamaIndex Reader → llama-index-readers-mineru/
│       flash mode: zero-token quick start
│       precision mode: OCR, tables, formulas, and higher fidelity

# Linux / macOS
curl -fsSL https://cdn-mineru.openxlab.org.cn/open-api-cli/install.sh | sh

# Windows (PowerShell)
irm https://cdn-mineru.openxlab.org.cn/open-api-cli/install.ps1 | iex

mineru-open-api flash-extract report.pdf

# First-time setup
mineru-open-api auth

# Extract to stdout
mineru-open-api extract paper.pdf

# Save all resources (images/tables) to directory
mineru-open-api extract report.pdf -o ./output/

# Export to multiple formats
mineru-open-api extract report.pdf -f docx,latex,html -o ./results/

mineru-open-api crawl https://www.example.com

# All PDFs in current directory
mineru-open-api extract *.pdf -o ./results/

# From a file list
mineru-open-api extract --list filelist.txt -o ./results/

pip install mineru-open-sdk

from mineru import MinerU

client = MinerU()
result = client.flash_extract("https://cdn-mineru.openxlab.org.cn/demo/example.pdf")
print(result.markdown)

from mineru import MinerU

client = MinerU("your-api-token")
result = client.extract("https://cdn-mineru.openxlab.org.cn/demo/example.pdf")
print(result.markdown)
print(result.images)  # extracted image list

go get github.com/opendatalab/MinerU-Ecosystem/sdk/go@latest

package main

import (
    "context"
    "fmt"
    mineru "github.com/opendatalab/MinerU-Ecosystem/sdk/go"
)

func main() {
    client := mineru.NewFlash()
    result, err := client.FlashExtract(
        context.Background(),
        "https://cdn-mineru.openxlab.org.cn/demo/example.pdf",
    )
    if err != nil {
        panic(err)
    }
    fmt.Println(result.Markdown)
}

client, err := mineru.New("your-api-token")
if err != nil {
    panic(err)
}
result, err := client.Extract(
    context.Background(),
    "https://cdn-mineru.openxlab.org.cn/demo/example.pdf",
)
if err != nil {
    panic(err)
}
fmt.Println(result.Markdown)

result, err := client.Extract(ctx, "./paper.pdf",
    mineru.WithModel("vlm"),
    mineru.WithLanguage("en"),
    mineru.WithPages("1-20"),
    mineru.WithExtraFormats("docx"),
    mineru.WithPollTimeout(10*time.Minute),
)
if err != nil {
    panic(err)
}
if err := result.SaveAll("./output"); err != nil {
    panic(err)
}

ch, err := client.ExtractBatch(ctx, []string{"a.pdf", "b.pdf"})
if err != nil {
    panic(err)
}
for result := range ch {
    fmt.Printf("%s: %s\n", result.Filename, result.State)
}

result, err := client.Crawl(ctx, "https://www.example.com")
if err != nil {
    panic(err)
}
fmt.Println(result.Markdown)

npm install mineru-open-sdk

import { MinerU } from "mineru-open-sdk";

const client = new MinerU();
const result = await client.flashExtract(
  "https://cdn-mineru.openxlab.org.cn/demo/example.pdf"
);
console.log(result.markdown);

import { MinerU } from "mineru-open-sdk";

const client = new MinerU("your-api-token");
const result = await client.extract(
  "https://cdn-mineru.openxlab.org.cn/demo/example.pdf"
);
console.log(result.markdown);
console.log(result.images);

import { MinerU, saveAll } from "mineru-open-sdk";

const client = new MinerU("your-api-token");
const result = await client.extract("./paper.pdf", {
  model: "vlm",       // "vlm" | "pipeline" | "html"
  language: "en",
  pages: "1-20",
  extraFormats: ["docx"],
  timeout: 600,
});
await saveAll(result, "./output");

for await (const result of client.extractBatch(["a.pdf", "b.pdf"])) {
  console.log(`${result.filename}: ${result.state}`);
}

const result = await client.crawl("https://www.example.com");
console.log(result.markdown);

{
  "mcpServers": {
    "mineru": {
      "command": "uvx",
      "args": ["mineru-open-mcp"],
      "env": {
        "MINERU_API_TOKEN": "your_key_here"
      }
    }
  }
}

MINERU_API_TOKEN=your_key mineru-open-mcp --transport streamable-http --port 8001

{
  "mcpServers": {
    "mineru": {
      "type": "streamableHttp",
      "url": "http://127.0.0.1:8001/mcp"
    }
  }
}

pip install langchain-mineru

from langchain_mineru import MinerULoader

loader = MinerULoader(source="demo.pdf")   # flash mode, no token needed
docs = loader.load()
print(docs[0].page_content[:500])
print(docs[0].metadata)

from langchain_mineru import MinerULoader

loader = MinerULoader(
    source="/path/to/manual.pdf",
    mode="precision",
    token="your-api-token",  # or set MINERU_TOKEN
    split_pages=True,
    pages="1-5",
)

docs = loader.load()
for doc in docs:
    print(doc.metadata.get("page"), doc.page_content[:200])

from langchain_mineru import MinerULoader
from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_openai import OpenAIEmbeddings
from langchain_community.vectorstores import FAISS

loader = MinerULoader(source="demo.pdf", split_pages=True)
docs = loader.load()

splitter = RecursiveCharacterTextSplitter(chunk_size=1200, chunk_overlap=200)
chunks = splitter.split_documents(docs)

vs = FAISS.from_documents(chunks, OpenAIEmbeddings())
results = vs.similarity_search("What are the key conclusions in this document?", k=3)

for r in results:
    print(r.page_content[:200])

pip install llama-index-readers-mineru

from llama_index.readers.mineru import MinerUReader

reader = MinerUReader()
documents = reader.load_data("https://cdn-mineru.openxlab.org.cn/demo/example.pdf")

print(documents[0].text[:500])
print(documents[0].metadata)

from llama_index.readers.mineru import MinerUReader

reader = MinerUReader(
    mode="precision",
    token="your-api-token",  # or set MINERU_TOKEN
    pages="1-20",
)
documents = reader.load_data("/path/to/paper.pdf")

from llama_index.core import VectorStoreIndex
from llama_index.readers.mineru import MinerUReader

reader = MinerUReader(split_pages=True)
documents = reader.load_data("/path/to/paper.pdf")

index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine()
response = query_engine.query("Summarize the main findings of this document")
print(response)